Development and Validation of Tadalafil Determination in Human Plasma by HPLC-MS Method
Bibliographic record
Abstract
Introduction. Tadalafil is a drug used to treat erectile dysfunction. For the quantitative determination of tadalafil in human plasma are used methods of high performance liquid chromatography with ultraviolet and tandem mass spectrometric detection, during the analytical part of pharmacokinetic studies. In the majority of the considered methods the method of liquid-liquid extraction and the method of solid-phase extraction are used, these methods are difficult and expensive. Therefore, the method of protein precipitation was considered as sample preparation. This method is simple and there is important to analysis a lot of clinical samples in bioequivalence studies. Aim. The aim of this study is to develop method for the quantitative determination of tadalafil in human plasma by HPLC-MS for the analytical part of pharmacokinetic studies. Materials and methods. Quantitative determination of tadalafil in plasma by HPLC-MS. A sample was prepared using acetonitrile protein precipitation. Results and discussion. This method was validated by next validation parameters: selectivity, matrix effect, calibration curve, accuracy, precision, lower limit of quantification, carry-over and stability. Conclusion. The method of the quantitative determination of tadalafil in human plasma was developed and validated by HPLC-MS. The analytical range of the was 5,00–1000,00 ng/ml tadalafil in plasma. Method could be applied to determination of tadalafil in plasma for PK and BE studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".